We describe a novel integration of Planning with Probabilistic State Estimation and Execution resulting in a unified representational and computational framework based on declarat...
Conor McGann, Frederic Py, Kanna Rajan, John Ryan,...
This paper presents a Function Word centered, Syntax-based (FWS) solution to address phrase ordering in the context of statistical machine translation (SMT). Motivated by the obse...
We describe how simple, commonly understood statistical models, such as statistical dependency parsers, probabilistic context-free grammars, and word-to-word translation models, c...
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. Dete...
We analyze the amount of information needed to carry out model-based recognition tasks, in the context of a probabilistic data collection model, and independently of the recogniti...